Ultrasound imaging apparatuses which perform imaging of a three-dimensional structure inside an object using ultrasound waves are widely utilized in the field of medicine as inexpensive ultrasound diagnostic apparatuses with few side effects.
Due to improvements in ultrasound imaging technology, performances of ultrasound diagnostic apparatuses are improving quickly each year. As a technique for further improving such performances, an image reconstruction technique using a DCMP (Directionally Constrained Minimization of Power) method is being studied. The DCMP method described herein is also known as the CAPON method.
The DCMP method is an adaptive signal processing technique developed as an adaptive antenna technique. The DCMP method involves adaptively adjusting directionality of reception under a constraint of maintaining a constant reception gain of radio waves that arrive from a desired direction to minimize power of all reception signals including constant interfering waves. According to this method, since the ratio of interfering wave power to signal power can be minimized, a signal with favorable SN can be received.
For example, a specific calculation according to the DCMP method can be approximately executed by following the steps below:
(1) Perform delaying on ultrasound reception signals received by a plurality (n number) of receiving elements to match phases so that n number of ultrasound reception signals originating from a same target position are aligned at the same time instant.
(2) Convert n number of reception signals with matched phases into complex signals. For the sake of the following description, n number of complex signals at a time instant t will be denoted as a received complex vector X[t] having n components.
(3) Based on the received complex vector X[t], calculate a complex correlation matrix A[k] at a constant time period T clock. k denotes the number of time intervals each having a period T, and the formula for calculating this matrix is represented by Expression (1) below:
                    [                  Math          .                                          ⁢          1                ]                                                                      A          ⁡                      [            k            ]                          =                              ∑                          t              =              kT                                      kT              +              T              -              1                                ⁢                                    X              ⁡                              [                t                ]                                      ⁢                                          X                ⁡                                  [                  t                  ]                                            H                                                          (        1        )            where the superscript H of X[t] denotes a transpose complex conjugate of a vector.
(4) Calculate an optimal weight vector W[k] using the matrix A[k] and a known constraint vector C. The formula for calculating formula the optimal weight vector is represented by Expression (2):
                    [                  Math          .                                          ⁢          2                ]                                                                      W          ⁡                      [            k            ]                          =                                                            A                ⁡                                  [                  k                  ]                                                            -                1                                      ⁢            C                                              C              H                        ⁢                                          A                ⁡                                  [                  k                  ]                                                            -                1                                      ⁢            C                                              (        2        )            where the superscript −1 of A[k] denotes an inverse matrix of A[k]. In addition, the constraint vector C is a known vector which specifies an arrival direction of a signal and which normally sets all components of a delayed output signal to 1.
(5) Calculate a constrained minimum power Pow[k] using Expression (3) based on the optimal weight vector W[k] and the received complex vector X[t]:
                    [                  Math          .                                          ⁢          3                ]                                                                      Pow          ⁡                      [            k            ]                          =                              1            2                    ·                                    ∑                              t                =                kT                                            kT                +                T                -                1                                      ⁢                                                                                                                      X                      ⁡                                              [                        t                        ]                                                              H                                    ⁢                                      W                    ⁡                                          [                      k                      ]                                                                                                  2                                                          (        3        )            
(6) Calculate a logarithm of the power Pow[k] and adopt the logarithm as a gray value q of a kth pixel of an output line image. The formula for calculating this logarithm is represented by Expression (4):q=Log [Pow[k′″  (4)
Although not an essential process, this logarithmic conversion is normally performed in order to facilitate visualization of the output image.
Moreover, while a spatial averaging process on the matrix A and a process of adding a small positive number to on-diagonal elements are performed in combination with the steps described above in an actual calculation, these processes will be omitted herein for the sake of brevity. In addition, the calculation formulas described above may sometimes be modified in various ways in order to improve performance of the DCMP method. Therefore, the calculation formulas described above merely represent an example of the DCMP method and are not intended to limit the scope of the present invention.
Performing the calculations described above enables image reconstruction based on the DCMP method and produces an image with improved resolution and contrast in comparison to a reconstructed image according to a normal delay-and-sum method. However, achieving practical use of the DCMP method requires a small and inexpensive signal processing apparatus that is capable of processing in real time a tremendous amount of complicated calculations represented by Expressions (1) to (3). In reality, the difficulty of realizing such an apparatus has prevented the DCMP method from being put to practical use.
A DCMP method using a beamspace method is being studied as an important method for reducing the tremendous amount of calculations. NPL 1 (see below) proposes a beamspace method using DFT (Discrete Fourier Transform). A beamspace method using DFT involves performing a Fourier transform by multiplying a delayed input signal vector X[t] by a Butler matrix B and using a Fourier coefficient corresponding to a low-frequency portion of the product as an input X[t] of the DCMP method.
NPL 1 describes that an approximately equivalent performance can be produced even when an original input signal has a large number of channels such as 128 channels by using three Fourier transform coefficients at the most. Among the calculation steps described above, the calculation amount of Expression (2) (that is, the amount of calculation involved in performing Expression (2)) is approximately proportional to the cube of the number of input channels and hence is particularly enormous. However, if the input of 128 channels can be reduced to three channels, a dramatic reduction in the calculation amount to 1/77672 can be achieved. Therefore, a DCMP method using the beamspace method is considered to be an important approach toward putting the DCMP method into practical use.
In addition, as another means to speed up adaptive signal processing, PTL 1 (see below) discloses a configuration in which a data thinning unit that reduces the amount of data is provided in a stage preceding an adaptive signal processor in order to reduce the amount of calculation of adaptive signal processing by reducing the amount of inputted data.